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Comment by nicky0 | Hacker News Reader

That’s very interesting. I assumed it was something about the fact that it is a language model rather than a calculating machine. So printing 44 asterisks instead of 40 is kind of close.

I wonder if would it be possible to teach the machine to recognise situations it’s better at and be less confident other answers? Or does it need to be confident about everything in order to produce good answers where it does.

It’s kind of funny how confident chatgpt is about giving out bullshit, and then even when you correct it, it says oh I’m terribly sorry, here is definitely the correct answer this time and then it gives you another wrong answer. Just an observation, I realise it is just a tool that you have to understand the limitations of.

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> here is definitely the correct answer this time and then it gives you another wrong answer.

My favorite is when it gets into some weird context loop, apologizes and claims to have corrected an issue, but gives you literally, character-for-character, the same answer it gave before.

Fortunately, it mostly happens to me when I am asking particularly ambiguous or weird questions -- e.g., asking for any assembly in AT&T/GAS syntax seems to always go wrong, not necessarily in terms of the logic itself, but rather that it ends up mixing Intel and AT&T, or asking explicitly for POSIX-compliant shell often gives weird Bash/GNUisms, presumably since so many StackOverflow posts seem to conflate all shells with Bash and always expect GNU coreutils.

We can check our answers, we can spit out bullshit like it does but then take the time to check them. It has no process for checking the answers or analyzing them and I'd rather not ask it how confident it is because that's just not what I care about.

I find it amazing that it can actually sort of run code "in its head", all the code output it does is not actually run through an interpreter but it's still pretty close if not perfect each time. But trying to run code with it is mostly for kicks, rather I asked it to produce a simple API for me and then produce a python script that tests it. it had no bugs and I could check it myself fairly fast; certainly faster than it would've taken me to write all that code without any bugs. I'd have had to check my own code for bugs anyway.

So if you accept that chatGPT is sort of like a guy that looked over millions of programmers shoulders but never actually communicated with any of them to understand the code, it has a perfect memory while not being able to compute much in its head then it can still be a great tool. Just understand its limitations and its advantages. Just because it can't reverse a string in its head doesn't mean it's "dumb" or not useful for everyday tasks.

I code with GitHub Copilot. I liken it to pair programming with an brilliant, insigntful & more experienced colleague who is always slightly drunk.

So basically a chat routine that’s been designed to hit the Ballmer peak.

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